1 Preface

This volume contains the full computer tabulations for the 2014 Wave 2 Technology Tracker, study, which has been run by Saville Rossiter-Base on behalf of Ofcom. The objective of the survey is to track the attitudes and behaviour of the general public with respect to the residential telecommunications market as well as broadcasting more generally.

Quadrangle Operations interviewed a quota sample of 2,877 adults, aged 16+, in the UK. Interviews were carried out across 231 different sampling points in the UK, face-to-face, in-home. All interviews were conducted between 12th May and 26th July 2014.

The data are initially weighted to correct the over-representation of nations, regions and areas to produce a geographically representative sample. They are then weighted by age, gender, social class, working status, and region to match the known population profile.

Details of the sampling frame, research methodology, and weighting procedures are outlined in the following pages. A note on statistical reliability is also included.

Sample Design

To ensure consistency with trend data, the sample approach to sampling has been used as in previous waves, using Output Areas (OAs) as the basic building block for sampling, then using quota control by three key variables (age, gender and SEG) to control the sample interviewed within each sampling point.

First Stage

The OAs in the UK were grouped into sampling units (SUs), which were then were stratified by region and rural/urban:

- firstly, all the SUs were sorted by region,
- the SUs were then sorted within region by rural/urban.

The sample extracted was checked for close correspondence to the UK population on two key variables:

- Deprivation Index for Great Britain. Currently there is no deprivation index for Northern Ireland.
- Cable/ non-cabled area

Since region has been used as the first sorting variable, regional distribution of SUs will be more or less in proportion to the number of residential addresses in each region. Second stage The size of a SU is measured by the number of addresses it contains. The SUs were selected with a probability proportionate to size. This ensures that all households within an SU have an equal chance of being selected, regardless of the size of the SU in which a household is situated. The number of interviews per SU was 12.

Quotas The following quotas were set (within each SU) to represent the population within that SU, which means the overall quotas across the UK will closely match the UK population. Quotas were set using 2011 Census data for Great Britain and Northern Ireland.

- Age (16-24, 25-44, 45+)
- Socio-economic grade (SEG)
- Gender

Fieldwork Interviewers were provided with specific addresses. The average SU contains around 130 households in England and Wales and 160 households in Scotland, thus affording tight control over the addresses the interviewers called at. All interviews were conducted in the home, using pen and paper.

Reporting The sample is drawn on the basis of households within SUs, while quotas are set on the basis of adult population profiles. The data is then weighted to the profile of UK adults and so the data is representative of adults aged 16+. Therefore, when reporting it is necessary to state that the data represents the percentage of adults rather than the percentage of households. Weighting

The data are weighted to the national UK profile using target rim weights for age, gender, socio-economic group (SEG), working status, region and cable/ non-cable. The following table shows the initial unweighted sample and the final weighted sample profile.

| Figures are based on UK adults | % Weighted | % Unweighted | |-------------------------------|------------|--------------| | | Profile | Interviews achieved | | Gender – Male 16+ | 48% | 48% | | Gender – Female 16+ | 52% | 52% | | Age – 16-34 | 33% | 28% | | Age – 35-54 | 35% | 32% | | Age – 55+ | 33% | 40% | | SEG – AB | 25% | 21% | | SEG – C1 | 30% | 30% | | SEG – C2 | 18% | 22% | | SEG – DE | 27% | 27% | | Working Status – working | 56% | 47% | | Working Status – not working | 43% | 53% | | Region – London | 12% | 9% | | Region – South East | 14% | 9% | | Region – East of England | 9% | 9% | | Region – South West | 8% | 9% | | Region – East Midlands | 7% | 9% | | Region – West Midlands | 9% | 9% | | Region – Yorkshire & Humber | 8% | 9% | | Region – North East | 4% | 3% | | Region – North West | 11% | 6% | | Region – Scotland | 9% | 9% | | Region – Wales | 5% | 9% | | Region – Northern Ireland | 3% | 9% | | Cable | 51% | 47% | | Non cable | 49% | 53% |

The percentages described above as ‘% Weighted’ are the targets used to weight the data. The figures for age, gender and location are taken from the 2001 Census. Cable/ non cable figures come from published data on the proportion of UK households in cabled areas, and SEG profiles come from NRS published data. The ‘% Unweighted’ column shows the actual percentage of interviews achieved in the May/ June/ July 2014 fieldwork. 2 Appendix A – Deprivation

Business Geographics’ ‘Small Area Deprivation Index’ is designed to detect ‘pockets’ of deprivation within wards. The deprivation index is created using a combination of socio-economic variables. Please note that the deprivation index only applies to Great Britain.

The index composition score is based on the following four variables:

1. Unemployment – unemployed residents
2. Overcrowding – households with more than one person per room
3. Non-car ownership – households without a car
4. Non-home ownership – households not owning (or buying) their own home

The deprivation index ranges from 0, equalling the least deprived, to 100, equalling the most deprived. This is broken down into a high/medium/low classification for the overall population. The higher the index, the more deprived the area.

Wave 2 2014 fieldwork achieved the following break-down of interviews:

| Deprivation Level | GB Profile (SU based) | GB Interviews achieved: Weighted | GB Interviews achieved: Unweighted | |-------------------|-----------------------|---------------------------------|----------------------------------| | Low Deprivation (0-33.33) | 61% | 61% | 62% | | Medium Deprivation (33.34 – 66.66) | 36% | 37% | 36% | | High Deprivation (66.67 – 100) | 3% | 2% | 2% | 3 Appendix B – Quotas

The following quotas were set at the outset of the project:

| Adults 16+ | Quotas set | Interviews achieved May-July 2014: Weighted | Interviews achieved May-July 2014: Unweighted | |------------|------------|---------------------------------------------|---------------------------------------------| | Gender – Male | 49% | 48% | 48% | | Gender – Female | 51% | 52% | 52% | | Age – 16-24 | 14% | 15% | 13% | | Age – 25-44 | 31% | 37% | 32% | | Age – 45-64 | 34% | 29% | 30% | | Age – 65+ | 22% | 20% | 25% | | SEG – AB | 23% | 25% | 21% | | SEG – C1 | 31% | 30% | 30% | | SEG – C2 | 22% | 18% | 22% | | SEG – DE | 26% | 27% | 27% |

4 Appendix C - Guide to Statistical Reliability

The variation between the sample results and the “true” values (the findings that would have been obtained if everyone had been interviewed) can be predicted from the sample sizes on which the results are based, and on the number of times that a particular answer is given. The confidence with which we can make this prediction is usually chosen to be 95%, that is, the chances are 95 in 100 that the “true” values will fall within a specified range. However, as the sample is weighted, we need to use the effective sample size (ESS) rather than actual sample size to judge the accuracy of results. The following table compares ESS & actual samples for some of the main analysis groups.

| | Actual | ESS | |--------------------------|--------|------| | Total | 2,877 | 2,357| | URBANITY: RURAL | 470 | 374 | | URBANITY: URBAN | 2,407 | 1,995| | GENDER: MALE | 1,369 | 1,127| | GENDER: FEMALE | 1,508 | 1,230| | AGE: 16-24 | 384 | 320 | | AGE: 25-44 | 916 | 765 | | AGE: 45-64 | 860 | 716 | | AGE: 65-74 | 346 | 283 | | AGE: 75+ | 371 | 307 | | SEG – AB | 608 | 512 | | SEG - C1 | 855 | 704 | | SEG - C2 | 621 | 505 | | SEG - DE | 785 | 652 | | HOUSEHOLD INCOME: UNDER £11.5K | 497 | 407 | The table below illustrates the required ranges for different sample sizes and percentage results at the “95% confidence interval”:

| Effective sample size | 10% or 90% | 20% or 80% | 30% or 70% | 40% or 60% | 50% | |-----------------------|------------|------------|------------|------------|-----| | ± | ± | ± | ± | ± | | | 2,357 (All respondents)| 1.2% | 1.6% | 1.9% | 2.0% | 2.1%| | 1,127 (Male) | 1.8% | 2.4% | 2.7% | 2.9% | 3.0%| | 704 (SEG C1) | 2.3% | 3.0% | 3.5% | 3.7% | 3.8%| | 374 (Rural) | 3.1% | 4.1% | 4.7% | 5.1% | 5.2%|

For example, if 30% or 70% of a sample of 2,357 gives a particular answer, the chances are 95 in 100 that the “true” value will fall within the range of ± 1.9 percentage points from the sample results.

When results are compared between separate groups within a sample, different results may be obtained. The difference may be “real”, or it may occur by chance (because not everyone has been interviewed). To test if the difference is a real one – i.e. if it is “statistically significant” – we again have to know the size of the samples, the percentages giving a certain answer and the degree of confidence chosen. If we assume “95% confidence interval”, the difference between two sample results must be greater than the values given in the table below to be significant: | Sample sizes being compared (sub-groups or trends) | 10% or 90% | 20% or 80% | 30% or 70% | 40% or 60% | 50% | |--------------------------------------------------|------------|------------|------------|------------|-----| | 1,127 v 1,230 (male vs. female) | 2.4% | 3.2% | 3.7% | 4.0% | 4.0%| | 512 v 704 (SEG AB vs. C1) | 3.4% | 4.6% | 5.2% | 5.6% | 5.7%|